Enhancing Instructional Quality: Leveraging Computer-Assisted Textual Analysis to Generate In-Depth Insights from Educational Artifacts

arXiv:2403.03920v1 Announce Type: cross
Abstract: This paper explores the transformative potential of computer-assisted textual analysis in enhancing instructional quality through in-depth insights from educational artifacts. We integrate Richard Elmore's Instructional Core Framework to examine how artificial intelligence (AI) and machine learning (ML) methods, particularly natural language processing (NLP), can analyze educational content, teacher discourse, and student responses to foster instructional improvement. Through a comprehensive review and case studies within the Instructional Core Framework, we identify key areas where AI/ML integration …

abstract analysis artificial artificial intelligence arxiv computer core cs.ai cs.cl cs.hc educational framework generate insights intelligence language machine machine learning natural natural language paper quality richard textual through type